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New Frontiers in Mining Complex Patterns [electronic resource] : Third International Workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers / edited by Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 8983 | Lecture Notes in Computer Science ; 8983Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XII, 211 p. 61 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319178769
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.312 23
LOC classification:
  • QA76.9.D343
Online resources: In: Springer Nature eBookSummary: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2014, held in conjunction with ECML-PKDD 2014 in Nancy, France, in September 2014. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: classification and regression; clustering; data streams and sequences; applications.
Item type: E-BOOKS
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This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2014, held in conjunction with ECML-PKDD 2014 in Nancy, France, in September 2014. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: classification and regression; clustering; data streams and sequences; applications.

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